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GitHub / autodistill / autodistill
Images to inference with no labeling (use foundation models to train supervised models).
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/autodistill%2Fautodistill
Stars: 1,566
Forks: 122
Open Issues: 32
License: apache-2.0
Language: Python
Repo Size: 2.49 MB
Dependencies:
22
Created: 12 months ago
Updated: 14 days ago
Last pushed: 14 days ago
Last synced: 14 days ago
Commit Stats
Commits: 194
Authors: 11
Mean commits per author: 17.64
Development Distribution Score: 0.294
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/autodistill/autodistill
Topics: auto-labeling, computer-vision, deep-learning, foundation-models, grounding-dino, image-annotation, image-classification, instance-segmentation, labeling-tool, machine-learning, model-distillation, multimodal, object-detection, pytorch, segment-anything, yolov5, yolov8
Files
Dependencies
- actions/cache v3 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- actions/checkout v3 composite
- actions/setup-python v2 composite
- actions/checkout v3 composite
- actions/setup-python v2 composite
- actions/first-interaction v1.1.1 composite
- Pillow >=7.1.2
- PyYAML >=5.3.1
- click *
- opencv-python >=4.6.0
- supervision *
- tqdm *
- lodash ^4.17.21
- Pillow >=7.1.2
- PyYAML >=5.3.1
- click *
- opencv-python >=4.6.0
- supervision *
- tqdm *
- lodash 4.17.21